Data visualization extensibility architecture

ABSTRACT

An extensibility framework for enabling the creation of new visualizations and the extension of existing visualizations is provided to improve the functionality of a computer. According to aspects, the architecture enables building data visualizations via a one-directional chain of separate stages that have simple input and output interfaces. The described extensibility architecture enables quick and simple extensibility of visualization types via series layouts that are independent of the rest of the architecture. The extensibility architecture allows for the compositing of features in such a way that allows clients to add additional functionality and the build-out of visualization types via a multiplicative behavior of chaining capabilities together. Accordingly, series layouts can be plugged into the data visualization platform in a generic way. The architecture is operable to work in multiple environments, and is not biased toward a single client.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application No. 62/063,741, titled “Data Visualization” filed Oct. 14, 2014.

BACKGROUND

Data visualization is a process for graphically representing data in a visualization, for example, a chart, an infographic, a map, a gauge, etc. Typically, when providing extensions (e.g., new visualization types) to a charting engine, large development costs were entailed, for example, in authoring the visualization and in the integration of the visualization by the client. Implementing new visualization types or versioning existing visualization types was therefore labor intensive and costly. Existing visualization could become unwieldy as their functionalities expanded and may be incompatible with newer or older data visualization clients, thus limiting the functionality of the device running the client or forcing the use of unwieldy workarounds.

It is with respect to these and other considerations that examples will be made.

SUMMARY

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description section. This summary is not intended to identify all features of the claimed subject matter, nor is it intended as limiting the scope of the claimed subject matter.

An architecture for creating new visualizations and extending existing visualizations within a data visualization platform architecture is provided. According to an aspect, the architecture enables building of a data visualization (e.g., a chart, an infographic, a map, a gauge, etc) via a one-directional chain of separate stages, each stage having a simple input interface and output interface. Aspects of the present disclosure provide an extensibility architecture that enables quick and simple extensibility of visualization types via series layouts that are independent of the rest of the architecture. The extensibility architecture allows for the compositing of features to enable clients to add additional functionality and build out of visualization types via a multiplicative behavior of chaining capabilities together. Accordingly, series layouts can be plugged into the data visualization platform in a generic way.

The architecture of the data visualization platform isolates the series layout logic from the rest of the system, such that each part has a simplistic view of other parts and therefore cannot become intertwined. According to several aspects, series layouts take as input a set of data plus a surface description (e.g., axes, coordinate space, resolution/dpi, etc.) and produce as output a collection of annotated geometry. A benefit of this design is a lower engineering cost per layout, enabling more visualization types to be produced quicker and with higher quality. Another benefit is the ability to version the series layouts to be forward and backward compatible while delivering better-than-linear scalability with respect to the size of the data set, as well as minimizing rasterization costs. Each layout in the platform takes into consideration the target surface dimension and axes to produce the minimal output without assistance from the client.

Examples may be implemented as a computer process, a computing system, or as an article of manufacture such as a computer program product or computer readable media. The computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process.

The details of one or more aspects are set forth in the accompanying drawings and description below. Other features and advantages will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that the following detailed description is explanatory only and is not restrictive of other aspects of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate various aspects of the present disclosure. In the drawings:

FIG. 1 illustrates an extensible data visualization framework leveraging an architecture having a unidirectional pipeline in which information flows;

FIG. 2 illustrates a pipelined architecture in which data flows in a single direction;

FIG. 3 is a flow chart showing general stages involved in a method for implementing an extendable framework;

FIG. 4 is an example block diagram illustrating physical components of a computing device;

FIGS. 5A and 5B are simplified block diagrams of a mobile computing device; and

FIG. 6 is a simplified block diagram of a distributed computing system.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the following description to refer to the same or similar elements. While aspects of the disclosure may be described, modifications, adaptations, and other implementations are possible. For example, substitutions, additions, or modifications may be made to the elements illustrated in the drawings, and the methods described herein may be modified by substituting, reordering, or adding stages to the disclosed methods. Accordingly, the following detailed description does not limit the present disclosure, but instead, the proper scope of the disclosure is defined by the appended claims. Examples may take the form of a hardware implementation, or an entirely software implementation, or an implementation combining software and hardware aspects. The following detailed description is, therefore, not to be taken in a limiting sense.

An architecture for creating new visualizations and extending existing visualizations within a data visualization platform architecture is provided. According to an aspect, the architecture enables building of a data visualization (e.g., a chart, an infographic, a map, a gauge, etc.) via a one-directional chain of separate stages, each stage having a simple input interface and output interface. Aspects of the present disclosure provide an extensibility architecture that enables quick and simple extensibility of visualization types via series layouts that are independent of the rest of the architecture. The extensibility architecture enables the provision of extension (e.g., new visualization types) to a charting engine without the large development costs previously entailed in authoring and integrating the visualization into the client. The extensibility architecture allows for the compositing of features to enable clients to add additional functionality and build out of visualization types via a multiplicative behavior of chaining capabilities together. Accordingly, series layouts can be plugged into the data visualization platform in a generic way.

The data visualization platform is operable to work with multiple environments, rendering stacks, and data back ends, and therefore, is not biased toward a single client. Clients have their own unique UI and personality requirements that are complimentary to their environments. For scenarios where clients add object oriented user interfaces (OOUI) to a visualization, placeholder objects are supported, which have a fixed size and bound position which can potentially affect layout.

The data visualization platform provides a collection of layouts and the ability to easily add interactive experiences around them. The centralization of the layouts enables a high degree of visual fidelity, performance, and compatibility across disparate clients and environments. Centralization also enables broader and more rapid innovation through content delivered via services and other means.

The architecture of the data visualization platform cleanly isolates the series layout logic from the rest of the system, such that each part has a simplistic view of other parts and therefore cannot become intertwined.

Series layouts have a simple set of inputs and outputs. According to several aspects, series layouts take as input a set of data plus a surface description (e.g., axes, coordinate space, resolution/dpi, etc.) and produce as output a collection of annotated geometry. A benefit of this design is a lower engineering cost per layout, enabling more visualization types to be produced quicker and with higher quality. Another benefit is the ability to version the series layouts to be forward and backward compatible while delivering better-than-linear scalability with respect to the size of the data set, as well as minimizing rasterization costs. Each layout in the platform takes into consideration the target surface dimension and axes to produce the minimal output without assistance from the client.

A series layout is capable of describing its basic needs so that the client and core engine can plug it in appropriately. Basic needs of a series layout include required data dimensions and coordinate systems (e.g. x/y/r+Cartesian, x/y+Radial, x/y+Cartesian), and capability metadata, such as, for example, “I'm a scientific chart,” “I'm appropriate only for small data sets,” or “Goal seek doesn't make sense for me.” The capabilities are best communicated via property tags, thereby simplifying versioning. The core engine will apply default behaviors in the absence of a property.

As described above, the series layouts exposed by the visualization platform are separated from the core engine and have their own interfaces. These interfaces are forward and backward compatible because they are commodities acquired to build dynamic document content and therefore are expected to have the same level of compatibility as the documents themselves. To support versioning of the series layouts, the isolation of the layouts from the core engine is leveraged; according to aspects, there are only a small set of internal interfaces that need to be versioned. With only a small set to worry about, the complexity of versioning is greatly reduced. Versioning of interfaces may be done using the usual design patterns: new interfaces inherit from old interfaces, and interfaces expose a ‘version’ property that may be queried to ensure backward and forward compatibility between the core engine and the series layouts. Several versions of a series layout may be included within the data visualization platform, which are operable to be chosen by the core engine based on its version or the version of the client.

Pluggability is also possible with proper versioning. Clients running an older version of the data visualization platform are able to consume newer layouts installed to a central repository. Knowledge of specific layouts is therefore not hard-coded into each client, but rather a discovery step at boot determines which layouts are currently installed that a client can choose between.

FIG. 1 illustrates a pipelined architecture 100 in which data flows in a single direction. As illustrated, the architecture 100 has a unidirectional pipeline 110. As is illustrated in the unidirectional pipeline 110, information flows through several stages, such as, for example, a data transform stage 120, a layout transform stage 130, and a geometry transform stage 140, in which, various extensibility features, functionalities, and modules can be inserted in. According to aspects, at each stage in the pipeline 110, there is a well-defined input and output interface, which is operable to output information according to a normalized format. The combination of being unidirectional and the normalization of input/output via interfaces provides extensibility, for example, by enabling a device providing data visualizations to extend a visualization's capabilities by inserting one or more transforms of the appropriate type into the chain (i.e., the pipeline 110).

Generally, a transform changes information from a first format into a second format. For example, transforms are operable to modify data received according to transmitter format to a receiver format, and vice versa. In another example, a transform is operable to modify data for it to define geometry (e.g., a chart is converted into definitional information of lines and Beziers to graphically represent the chart's data) or to customize a definition for geometry (e.g., to modify existing geometry to create customized geometry). In a further example, geometry can be modified by transforms to alter how it is rendered (e.g., a color or visual theme is applied, the original definition of lines and Beziers modified, etc.). According to aspects, transforms modify information within the pipeline 110 used to create a visualization 160 to affect new and different functionalities in a system providing data visualizations to create customized visualizations. Several transforms can be chained together to affect advanced functionalities and extend the operability of existing architectures.

For example, an architecture is extended by inserting data transforms 125, layout transforms 135, or geometry transforms 145. As an example, a visualization plotter can be made operable to receive data from arbitrary clients in arbitrary formats via an appropriate data transform 125. As another example, a client can plug in a feature, such as a “sketch effect” feature, where a visualization 160 can be drawn such that it looks as though it were hand drawn, wherein a geometry transform 145 takes the output of the layout transform stage 130 (i.e., the geometry) and then perturb the vectors and primitives comprising the geometry to look hand drawn. As a further example, a new chart type can be added by creating a new series layout 135B (e.g., in layout transform stage 130). Alternatively, an existing series layout 135B can be modified by inserting a layout transform 135 (e.g., a shared functionality 135A, or series layout 135B) to alter the geometry definitions used by the existing series layout 135B. Accordingly, a new charting experience that is unique to the client application is introduced that works with the rest of the pipeline 110, thereby extending the pipelined architecture 100.

Transforms are inserted to extend the pipelined architecture 100 by accepting the output of a first stage (e.g., intercepting the output of a first stage) and producing a customized output according to an expected format for a second stage. For example, when a second stage expects data according to a normalized format produced by a first stage, a transform that accepts data according to the normalized format and outputs data according to the normalized output can be inserted to affect a new feature or behavior in the second stage, without having to update the second stage. In another example, a transform is operable to output a customization according the second stage's expected normalized format after receiving data organized according to an arbitrary format. Accordingly, cross-version or cross-platform interoperability can be realized by extending the pipelined architecture 100.

The data transform stage 120 in the pipeline 110, is where data transforms 125 are optionally applied. According to aspects, the data transform stage 120 occurs as the client feeds data 150 to a data visualization platform to create the visualization 160. Data transforms 125A, 125B are illustrated as optional transforms that may be implemented to transform raw user data 150 into a normalized form ready for layout for the visualization 160. For example, data transforms 125 may include sorting, filtering, or converting the data 150 into a form that can be used a data visualization platform. In aspects where the data 150 is already in normalized form, data transforms 125 are not implemented, or a “pass-through” transform is used.

As illustrated in FIG. 1, the layout transform stage 130 is the next stage in the pipeline 110. According to aspects, the layout transform stage 130 occurs when rendering, hit testing, or other functions for which a layout of the visualization 160 is needed are performed. During the layout transform stage 130, objects within the visualization 160 are positioned, and their geometries are built. According to an aspect, layout transforms 135 take normalized data and build a hierarchical scene graph of visual elements comprised of annotated geometry or text. Layout transforms 135 include shared functionalities 135A (e.g., colorization, trend lines, data labels, and other functionalities used in common by data series within a visualization) and series layouts 135B, which create the annotated geometry for individual data series. In various examples, the annotated geometry is encoded with meta-information such that any renderer can have semantic understanding or context around the vectors. According to aspects, the outputted annotated geometry is then cached.

The geometry transform stage 140 in the pipeline 110 is where geometry transforms 145 are optionally applied. According to aspects, when a client interrogates a data visualization platform (e.g., to render the visualization 160, render animation, build interactivities etc.), the client may optionally insert one or more geometry transforms 145 to modify how the visualization 160 is rendered. As illustrated, one or more geometry transforms 145A, 145B may be inserted to modify the styling of the visualization, convert to pixel space, apply snapping, geometry culling, warp effects, hand drawn effects, projections, three-dimensional surface mapping, change the color of certain data points, etc. By inserting one or more geometry transforms 145, the appearance of a visualization 160 is altered, which, in some examples, effectively produces a new visualization type. For example, consider a bubble chart where a geometry transform 145 is injected that colorizes the chart based on areas of density, and accordingly transforms the bubble chart into a heat map visualization.

Because the data flow is segmented, a vast number of visualizations can be assembled via pipeline 110. As described above, the architecture 100 uses series layouts 135B (e.g., PieSeriesLayout, ScatterSeriesLayout, ColumnSeriesLayout, etc.) rather than chart layouts, which are a broader feature. A series layout 135B, lays out a series of data within the coordinate space of a visualization 160 to create the geometry that represents the data 150 in a series-by-series format. For example, a PieSeriesLayout is operable to output individual wedges representing an individual data series (i.e., the series-by-series format), whereas a PieChartLayout would only be operable to output an entire chart (i.e., all of the data series). The collection of series layouts 135B is not fixed. Various data visualization platforms and applications are enabled to determine which extensions are available, and can have series layouts 135B that are specific to their client.

According to an aspect, each series layout 135B is operable to expose a static set of read-only properties (e.g., annotations) that enable data visualization applications to intelligently determine how best to integrate the series layout 135B with the client's user interface (UI). For example, a data visualization application can use the read-only properties to query capabilities, recommended settings, and other contextual needs. For example, the annotations can inform the data visualization application what features are supported by the series layout 135B, what the limitations of the series layout 135B are, etc. For example, a series layout 135B may expose a property that describes what size of dataset is appropriate for a given series layout 135B (e.g., <10 data points, <1,000 data points, <1,000,000 data points, etc.). Accordingly, a UI that recommends chart types based on data would be influenced by such a property. For example, when a pie chart is designated as not an appropriate chart type for a large dataset, an example property of the PieSeriesLayout exposes, via annotations, that a pie chart is an inappropriate visualization for datasets with greater than, for example, fifty data points. Accordingly, the data visualization application is enabled to filter out the PieSeriesLayout from a list of series layouts 135B presented to a user to pick from if a dataset comprises more than fifty data points.

Series layouts 135B are independent of the rest of the visualization definition. According to an aspect, a series layout 135B is provided a limited view of the input information to only the information it needs to produce geometry, including data 150 and a coordinate space for the visualization 160 (e.g., a surface description, origin, directional axes, etc.). Each series layout 135B may be exposed and implemented via one interface. In turn, a single contextual interface is exposed to the series layout 135B, which comprises methods that tell the series layout 135B to build its geometry from the data 150, enumerate the geometry it produces, and provides methods to query meta-information, fetch data 150, and map data values to a position within a coordinate space of the visualization 160. The independence of series layouts 135B from the rest of the chart behavior and definition (e.g., data transforms 125, shared functionalities 135A, etc.) enables series layouts 135B to be delivered in a form that is forward and backward compatible with other versions of the architecture 100. For example, when a series layout 135B is incapable of interrogating a legend, a trend line, or other shared objects, the processes that create those objects can be updated independently of the series layouts 135B and vice versa. In further aspects, isolation of the series layout 135B from the shared functionalities 135A enables the addition of other coordinate spaces in the future that will continue to work with older series layouts 135B, and thus reduces the cost of versioning series layouts 135B. Benefits of isolation also include enabling the architecture 100 to add new features that ‘just work’ with pre-existing visualization layouts, which reduces the cost of building or versioning layouts.

The limited and simplified tasks of series layouts 135B enables the centralization of shared functionalities 135A (e.g., colorization, trend lines, data labels, and other functionalities used in common by data series within a visualization 160) without participation from the series layout 135B. Features added to the shared functionalities 135A can be composited with all series layouts 135B, and thus produce a vast number of visualization types.

A shared interface may used by series layouts 135B for inputs and settings shared in common, such as, for example, required data dimensions. According to other aspects, when there are settings that are specific to a particular series layout 135B that cannot be modelled generically, a custom interface is exposed via which custom inputs and settings can be configured. For example, there may be exceptions or one-off behaviors to the generic nature of the definitions used within the shared interface of the series layouts 135B.

FIG. 2 is an example block diagram of a system 200 operable to improve the functionality a computer providing data visualization via a data visualization platform 220. According to aspects, the system improves the functionality of a computer by implementing an extendable framework for creating new visualizations and extending existing visualization types. The data visualization platform 220 is illustrated as communicating with data 150, a client 210, and an output device 260. The data visualization platform 220 is illustrated as comprising a core engine 230, operable to build a visualization 160 from shared objects and geometry representative of the data 150, a series layout module 240, operable to create the geometry representative of the data 150, and an extension module 250, operable to provide additional transforms and functionalities to apply as the data 150 is processed.

The client 210 is operable to provided visualizations of data to a user and interactivity between the user and the data 150 and the user and the visualization 160. As illustrated the client 210 is operable to write to and read from the data 150, which is passed to the data visualization platform 220 with a surface description to produce the geometry for a visualization 160. According to aspects, the client 210 is further operable to query the extension module 250 for transforms to modify the data sent to the data visualization platform 220. In various examples, a data transform 125 preserves the data 150, but provides the data visualization with a normalized format of the data 150; only a transmitted copy of the data 150 is affected. Data transforms 125 are operable to extend the functionality of the client 210 and data visualization platform 220 and enable simpler versioning of each.

As illustrated, the client 210 is operable to receive geometry from the data visualization platform 220 and pass the geometry received to an output device 260 such as a monitor, screen, printer, or other display device to provide the visualization 160. For example, the client 210 may pass the geometry to the output device via an appropriate rendering Application Programming Interface (API). According to additional aspects, the client 210 is further operable to query the extension module 250 for transforms to modify the geometry received from the data visualization platform to extend the functionality of the core engine 230 and series layout module 240.

The data visualization platform 220 positions objects within the visualization and creates their geometries. In various aspects, a series layout module 240 comprises series layouts 135B that draw geometry for each series of data within a plot area in a specific format (e.g., columns for column series, markers for scatter series, bubbles for bubble series, etc.). According to aspects, the series layout module 240 is operable to produce annotated geometry from a limited and immutable view of the data 150 and surface description. That is, the series layout module 240 takes a set of data plus a surface description (e.g., visualization type, visualization size, client resolution/dpi, etc.) as inputs, and produces a collection of annotated geometry as output. In some aspects, the annotated geometry is cached in a series object, and the series layout module 240 is not invoked again unless layout is required. The core engine 230 is operable process the annotated geometry and to deliver shared functionalities (e.g., titles, axes, legends, colors, etc.) of the series and data points without assistance from the series layout module 240.

The input to the series layout module 240 comes in the form of a set of layout interfaces that expose only the information necessary to produce the annotated geometry (i.e., via the limited and immutable view). These interfaces are disconnected from the larger object model and therefore enforce strict isolation of the series layout module 240 from the rest of the system. Benefits of isolation include enabling the data visualization platform 220 to add new features that ‘just work’ with pre-existing visualization layouts, which reduces the cost of building or versioning layouts.

As discussed above, the extension module 250 is operable to provide additional transforms to apply to the data 150 and the geometry within the visualization 160. According to further aspects, the data transforms 125 and geometry transforms 145 discussed above are executed via a unidirectional pipeline 110 during the creation of the visualization 160 or during the presentation of the visualization 160. In various examples, the extension module 250 is operable to provide rendering APIs and communicate with output device 260 to present the visualization 160. According to further examples, extension module 250 is operable to provide simple data storage and persistence tools for data 150.

The extension module 250 may be inserted into an existing system to enable extensibility. For example, a new version of an extension module 250 can be added to replace a previous version or be added as a new module within the system 200. In another example, the extension module 250 includes several transforms, wherein each transform is designed to extend communication between different versions of the data visualization platform 220 and the client 210, such that the version of each does not impact the presentation of a visualization 160; appropriate transforms are provided to enable backwards and forwards compatibility. According an example set of transforms for enabling extensibility, a client 210 normally operable to send and receive information for visualizations based on chart layouts is enabled to communicate with a data visualization platform 220 operable to receive and send information based on series layouts via transforms; each component is enabled to manipulate information natively, and the client 210 is enabled to leverage the data visualization platform's 220 use of series layouts.

Although illustrated in FIG. 2 as part of the data visualization platform 220, in alternative aspects, the extension module 250 may be part of the client 210 or a standalone module.

FIG. 3 is a flow chart showing general stages involved in a method 300 for implementing an extendable framework. Method 300 begins at START 301 and proceeds to OPERATION 310 where an interface is exposed to receive input data 150. According to aspects, the interface is implemented for a series layout module 240 to building geometry for a visualization 160 defined by the data 150. An example interface exposes a limited and immutable view of the input data 150 according to a normalized format so that a series layout 135B operates only on those data which affect its output. Several series layouts 135B may be chained together to affect different portions of the data 150. In this way, new series layouts 135B are added to the chain to affect an extension of the data visualization platform 220 and its capabilities. Similarly, older versions of series layouts 135B may be removed from the chain and replaced by newer versions, which improves the versioning process.

In examples where there are settings specific to a particular series layout 135B (e.g., not included in the normalized format), method 300 proceeds to optional OPERATION 320, where a custom interface is exposed for custom settings to be configured.

Method 300 then proceeds to OPERATION 330, where a single contextual interface is exposed comprising methods to fetch data and plot data values to a position within the coordinate space of the visualization 160. As described above, the series layout 135B may have a limited and isolated view of the input state to comprise data and coordinate space. According to aspects, the contextual interface provides a surface description, operable to provide contextual information related to a client 210 providing a visualization 160.

At optional OPERATION 340, one or more data transforms 125 are optionally inserted for extensibility. For example, a data transform 125 that assembles or buckets/groups data 150 into categories or series may be inserted. Accordingly, after the data 150 is transformed, the categorized data can be plotted through one of the series layouts 135B that is appropriate for categorized data. In another example, a data transform 125 changes the data 150 from a first format to a second format. As will be understood, changing the format of the data 150 in some aspects does not affect the underlying values, merely how those values are presented (e.g., rearranging an array), and in other aspects, affects the underlying values to conform to the new format (e.g., the value of data initially formatted as a DOUBLE type variable is truncated or rounded when changed to an INTEGER type variable). The data transforms 125 are operable produce a customization of the data 150, such that the data 150 is received according to a normalized format.

At OPERATION 350 a set of annotated geometry is built. According to aspects, the annotated geometry includes graphical representations of the data 150, shared objects (axes, titles, data labels, etc.), and contextual information about these elements of the geometry. Several layout transforms 135 (e.g., shared functionalities 135A and series layouts 135B) may be chained together to create or modify the definitions of the graphical representations of data 150, the shared objects, and their annotations.

From OPERATION 350 the method 300 proceeds to OPERATION 360, where the annotations of the geometry exposed. According to aspects, the geometry is exposed via an interface that enables a client 210 to determine how best to integrate the series layout 135B with the client UI. For example, a data visualization application can use the annotations to query capabilities, recommended settings, and other contextual needs for the extensible framework, such as which geometry transforms 145 are available for a given geometry. In another example, the exposed annotations enable the assembly of the graphical representations of series of the data 150 and the shared objects into a coherent visualization 160. For example, the annotations may indicate portions of the geometry (e.g., lines, Beziers, figures, etc.) to which a data label is to be affixed within the visualization 160.

At OPERATION 370, the annotated geometry is cached. According to aspects, the annotated geometry is cached in privatized storage so that it can be enumerated or retrieved upon request. For example, the annotated geometry can be cached within the visualization 160 or within series objects, which privatize the storage of the geometry used to graphically represent a data series and may be stored in contiguous blocks of memory to improve the speed of retrieval.

At optional OPERATION 380, one or more geometry transforms 145 are optionally inserted for extensibility. For example, geometry transform 145 of a drawing effect can be applied that transforms the geometry to produce a new type of visualization 160. For example, a geometry transform 145 applies a drawing effect to convert a two-dimensional geometry for a column chart into a three-dimensional geometry. As will be understood, multiple geometry transforms 145 can be chained together to apply various combined effects. For example, a first geometry transform 145A may convert the geometry from two-dimensional to three-dimensional geometry and a second geometry transform 145B may affect the positioning of the three-dimensional columns within the coordinate space of the map. In another example, the geometry transform 145 combines several series objects into a chart object so that a rendering client 210 that is unable to process series objects can still render a visualization 160 comprising series objects. According to aspects, by adding and re-combining geometry transforms 145, new visualization types are produced to extend the architecture 100.

Geometry transforms 145 may leverage the exposed annotations. For example, annotations may call out area of interest to suggest styling cues, areas of interactivity, and data bindings. Accordingly, a geometry transform 145 may be suggested to a user or automatically implemented to change how an annotated area is rendered.

At OPERATION 390 the annotated geometry is rendered to provide the visualization 160. According to aspects, the annotated geometry is transmitted to a rendering API and subsequently passed to an output device 260 to provide the visualization 160. Method 300 ends at OPERATION 399.

While the present disclosure has been described in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a computer, those skilled in the art will recognize that the present disclosure may also be implemented in combination with other program modules. Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types.

The aspects and functionalities described herein may operate via a multitude of computing systems including, without limitation, desktop computer systems, wired and wireless computing systems, mobile computing systems (e.g., mobile telephones, netbooks, tablet or slate type computers, notebook computers, and laptop computers), hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, and mainframe computers.

In addition, the aspects and functionalities described herein may operate over distributed systems (e.g., cloud-based computing systems), where application functionality, memory, data storage and retrieval and various processing functions may be operated remotely from each other over a distributed computing network, such as the Internet or an intranet. User interfaces and information of various types may be displayed via on-board computing device displays or via remote display units associated with one or more computing devices. For example, user interfaces and information of various types may be displayed and interacted with on a wall surface onto which user interfaces and information of various types are projected. Interaction with the multitude of computing systems with which aspects of the disclosure may be practiced include, keystroke entry, touch screen entry, voice or other audio entry, gesture entry where an associated computing device is equipped with detection (e.g., camera) functionality for capturing and interpreting user gestures for controlling the functionality of the computing device, and the like.

FIGS. 4-6 and the associated descriptions provide a discussion of a variety of operating environments in which examples of the disclosure may be practiced. However, the devices and systems illustrated and discussed with respect to FIGS. 4-6 are for purposes of example and illustration and are not limiting of a vast number of computing device configurations that may be utilized for practicing aspects of the disclosure, described herein.

FIG. 4 is a block diagram illustrating physical components (i.e., hardware) of a computing device 400 with which examples of the present disclosure may be practiced. The computing device components described below may be suitable for the client device described above. In a basic configuration, the computing device 400 may include at least one processing unit 402 and a system memory 404. Depending on the configuration and type of computing device, the system memory 404 may comprise, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories. The system memory 404 may include an operating system 405 and one or more program modules 406 suitable for running software applications 450, such as client 210. According to an aspect, the system memory 404 may include the data visualization platform 220. The operating system 405, for example, may be suitable for controlling the operation of the computing device 400. Furthermore, aspects of the disclosure may be practiced in conjunction with a graphics library, other operating systems, or any other application program and is not limited to any particular application or system. This basic configuration is illustrated in FIG. 4 by those components within a dashed line 408. The computing device 400 may have additional features or functionality. For example, the computing device 400 may also include additional data storage devices (removable and non-removable) such as, for example, magnetic disks, optical disks, or tape. Such additional storage is illustrated in FIG. 4 by a removable storage device 409 and a non-removable storage device 410.

As stated above, a number of program modules and data files may be stored in the system memory 404. While executing on the processing unit 402, the program modules 406 (e.g., client 210, data visualization platform 220) may perform processes including, but not limited to, one or more of the stages of the method 300 illustrated in FIG. 3. Other program modules that may be used in accordance with examples of the present disclosure and may include applications such as electronic mail and contacts applications, word processing applications, spreadsheet applications, database applications, slide presentation applications, drawing or computer-aided application programs, etc.

Furthermore, examples of the disclosure may be practiced in an electrical circuit comprising discrete electronic elements, packaged or integrated electronic chips containing logic gates, a circuit utilizing a microprocessor, or on a single chip containing electronic elements or microprocessors. For example, examples of the disclosure may be practiced via a system-on-a-chip (SOC) where each or many of the components illustrated in FIG. 4 may be integrated onto a single integrated circuit. Such an SOC device may include one or more processing units, graphics units, communications units, system virtualization units and various application functionality all of which are integrated (or “burned”) onto the chip substrate as a single integrated circuit. When operating via an SOC, the functionality, described herein, may be operated via application-specific logic integrated with other components of the computing device 400 on the single integrated circuit (chip). Examples of the present disclosure may also be practiced using other technologies capable of performing logical operations such as, for example, AND, OR, and NOT, including but not limited to mechanical, optical, fluidic, and quantum technologies. In addition, aspects of the disclosure may be practiced within a general purpose computer or in any other circuits or systems.

The computing device 400 may also have one or more input device(s) 412 such as a keyboard, a mouse, a pen, a sound input device, a touch input device, etc. The output device(s) 414 such as a display, speakers, a printer, etc. may also be included. The aforementioned devices are examples and others may be used. The computing device 400 may include one or more communication connections 416 allowing communications with other computing devices 418. Examples of suitable communication connections 416 include, but are not limited to, RF transmitter, receiver, or transceiver circuitry; universal serial bus (USB), parallel, or serial ports.

The term computer readable media as used herein may include computer storage media. Computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, or program modules. The system memory 404, the removable storage device 409, and the non-removable storage device 410 are all computer storage media examples (i.e., memory storage.) Computer storage media may include RAM, ROM, electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other article of manufacture which can be used to store information and which can be accessed by the computing device 400. Any such computer storage media may be part of the computing device 400. Computer storage media does not include a carrier wave or other propagated data signal.

Communication media may be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media. The term “modulated data signal” may describe a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.

FIGS. 5A and 5B illustrate a mobile computing device 500, for example, a mobile telephone, a smart phone, a tablet personal computer, a laptop computer, and the like, with which aspects of the disclosure may be practiced. With reference to FIG. 5A, an example of a mobile computing device 500 for implementing the aspects is illustrated. In a basic configuration, the mobile computing device 500 is a handheld computer having both input elements and output elements. The mobile computing device 500 typically includes a display 505 and one or more input buttons 510 that allow the user to enter information into the mobile computing device 500. The display 505 of the mobile computing device 500 may also function as an input device (e.g., a touch screen display). If included, an optional side input element 515 allows further user input. The side input element 515 may be a rotary switch, a button, or any other type of manual input element. In alternative examples, mobile computing device 500 may incorporate more or less input elements. For example, the display 505 may not be a touch screen in some examples. In alternative examples, the mobile computing device 500 is a portable phone system, such as a cellular phone. The mobile computing device 500 may also include an optional keypad 535. Optional keypad 535 may be a physical keypad or a “soft” keypad generated on the touch screen display. In various aspects, the output elements include the display 505 for showing a graphical user interface (GUI), a visual indicator 520 (e.g., a light emitting diode), or an audio transducer 525 (e.g., a speaker). In some examples, the mobile computing device 500 incorporates a vibration transducer for providing the user with tactile feedback. In yet another example, the mobile computing device 500 incorporates peripheral device ports 540, such as an audio input (e.g., a microphone jack), an audio output (e.g., a headphone jack), and a video output (e.g., a HDMI port) for sending signals to or receiving signals from an external device.

FIG. 5B is a block diagram illustrating the architecture of one example of a mobile computing device. That is, the mobile computing device 500 can incorporate a system (i.e., an architecture) 502 to implement some examples. In one example, the system 502 is implemented as a “smart phone” capable of running one or more applications (e.g., browser, e-mail, calendaring, contact managers, messaging clients, games, and media clients/players). In some examples, the system 502 is integrated as a computing device, such as an integrated personal digital assistant (PDA) and wireless phone.

One or more application programs 550, for example, client 210, may be loaded into the memory 562 and run on or in association with the operating system 564. Examples of the application programs include phone dialer programs, e-mail programs, personal information management (PIM) programs, word processing programs, spreadsheet programs, Internet browser programs, messaging programs, and so forth. According to an aspect, the data visualization platform 220 may be loaded into memory 562. The system 502 also includes a non-volatile storage area 568 within the memory 562. The non-volatile storage area 568 may be used to store persistent information that should not be lost if the system 502 is powered down. The application programs 550 may use and store information in the non-volatile storage area 568, such as e-mail or other messages used by an e-mail application, and the like. A synchronization application (not shown) also resides on the system 502 and is programmed to interact with a corresponding synchronization application resident on a host computer to keep the information stored in the non-volatile storage area 568 synchronized with corresponding information stored at the host computer. As should be appreciated, other applications may be loaded into the memory 562 and run on the mobile computing device 500.

The system 502 has a power supply 570, which may be implemented as one or more batteries. The power supply 570 might further include an external power source, such as an AC adapter or a powered docking cradle that supplements or recharges the batteries.

The system 502 may also include a radio 572 that performs the function of transmitting and receiving radio frequency communications. The radio 572 facilitates wireless connectivity between the system 502 and the “outside world,” via a communications carrier or service provider. Transmissions to and from the radio 572 are conducted under control of the operating system 564. In other words, communications received by the radio 572 may be disseminated to the application programs 550 via the operating system 564, and vice versa.

The visual indicator 520 may be used to provide visual notifications or an audio interface 574 may be used for producing audible notifications via the audio transducer 525. In the illustrated example, the visual indicator 520 is a light emitting diode (LED) and the audio transducer 525 is a speaker. These devices may be directly coupled to the power supply 570 so that when activated, they remain on for a duration dictated by the notification mechanism even though the processor 560 and other components might shut down for conserving battery power. The LED may be programmed to remain on indefinitely until the user takes action to indicate the powered-on status of the device. The audio interface 574 is used to provide audible signals to and receive audible signals from the user. For example, in addition to being coupled to the audio transducer 525, the audio interface 574 may also be coupled to a microphone to receive audible input, such as to facilitate a telephone conversation. The system 502 may further include a video interface 576 that enables an operation of an on-board camera 530 to record still images, video stream, and the like.

A mobile computing device 500 implementing the system 502 may have additional features or functionality. For example, the mobile computing device 500 may also include additional data storage devices (removable and non-removable) such as, magnetic disks, optical disks, or tape. Such additional storage is illustrated in FIG. 5B by the non-volatile storage area 568.

Data/information generated or captured by the mobile computing device 500 and stored via the system 502 may be stored locally on the mobile computing device 500, as described above, or the data may be stored on any number of storage media that may be accessed by the device via the radio 572 or via a wired connection between the mobile computing device 500 and a separate computing device associated with the mobile computing device 500, for example, a server computer in a distributed computing network, such as the Internet. As should be appreciated such data/information may be accessed via the mobile computing device 500 via the radio 572 or via a distributed computing network. Similarly, such data/information may be readily transferred between computing devices for storage and use according to well-known data/information transfer and storage means, including electronic mail and collaborative data/information sharing systems.

FIG. 6 illustrates one example of the architecture of a system for providing data visualization as described above. Content developed, interacted with, or edited in association with the client 210 or data visualization platform 220 may be stored in different communication channels or other storage types. For example, various documents may be stored using a directory service 622, a web portal 624, a mailbox service 626, an instant messaging store 628, or a social networking site 630. The client 210 or data visualization platform 220 may use any of these types of systems or the like for providing data visualization, as described herein. A server 615 may provide the client 210 or data visualization platform 220 to clients 605A-C. As one example, the server 615 may be a web server providing the client 210 or data visualization platform 220 over the web. The server 615 may provide the client 210 or data visualization platform 220 over the web to clients 605 through a network 610. By way of example, the client computing device may be implemented and embodied in a personal computer 605A, a tablet computing device 605B or a mobile computing device 605C (e.g., a smart phone), or other computing device. Any of these examples of the client computing device may obtain content from the store 616.

Aspects of the present disclosure, for example, are described above with reference to block diagrams or operational illustrations of methods, systems, and computer program products according to aspects of the disclosure. The functions/acts noted in the blocks may occur out of the order as shown in any flowchart. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved.

The description and illustration of one or more examples provided in this application are not intended to limit or restrict the scope of the present disclosure in any way. The aspects, examples, and details provided in this application are considered sufficient to convey possession and enable others to make and use the best mode of present disclosure. The present disclosure should not be construed as being limited to any aspect, example, or detail provided in this application. Regardless of whether shown and described in combination or separately, the various features (both structural and methodological) are intended to be selectively included or omitted to produce an example with a particular set of features. Having been provided with the description and illustration of the present application, one skilled in the art may envision variations, modifications, and alternate examples falling within the spirit of the broader aspects of the general inventive concept embodied in this application that do not depart from the broader scope of the present disclosure. 

We claim:
 1. A computer-executed method for improving the functionality of a computer providing a data visualization according to an existing architecture, comprising: managing a pipelined flow of information, wherein the information is used to graphically represent data including series via a visualization, by inserting a transform into the pipelined flow to customize the visualization; receiving the data and a surface description of the visualization; creating geometry to graphically represent each series of the data within the visualization based on the surface description, wherein the transform customizes one or more of the geometry; and transmitting the customized geometry to a client operable to render the visualization in accordance with the transform.
 2. The computer-executed method of claim 1, wherein the inserted transform is a data transform, wherein the data transform modifies a format of the received data, wherein the data according to the modified format is operable to produce the customized geometry.
 3. The computer-executed method of claim 1, wherein the inserted transform is a geometry transform, wherein the geometry transform modifies how the customized geometry is rendered by the client.
 4. The computer-executed method of claim 1, wherein the inserted transform is a series layout, wherein the series layout modifies the created geometry to graphically represent at least one of the series of the data within the visualization.
 5. The computer-executed method of claim 1, wherein the client is operable to present a plurality of transforms to be inserted that are determined to be appropriate for the data based on features of each transform of the plurality of transforms, wherein each transform of the plurality of transforms includes annotations operable to indicate its features to the client.
 6. The computer-executed method of claim 5, wherein at least one of the plurality of transforms is inserted.
 7. The computer-executed method of claim 1, wherein the pipelined flow of information is unidirectional, wherein the information flows from the client, to a data visualization platform, operable to create the geometry, and flows back to the client, where the geometry is rendered within the visualization.
 8. The computer-executed method of claim 1, wherein the pipelined flow of information includes: a data transform stage, corresponding to receiving the data and the surface description of the visualization; a layout transform stage, corresponding to creating the geometry; a geometry transform stage, corresponding to rendering the visualization; and wherein the transform is operable to be inserted at each of the stages.
 9. A system for improving the functionality of a computer providing a data visualization according to an existing architecture, comprising: a processor; and a memory storage including instructions, which when executed by the processor cause the computing device to be operable to provide: a data visualization platform, including: a series layout module, operable to create geometry to graphically represent data series in a visualization; and a core engine, operable to: receive the data series and surface description of the visualization; transmit the data series and the surface description to the series layout module to create the geometry based on the surface description; and assemble the visualization based on the geometry and the surface description; and an extension module, operable to insert transforms into the data visualization platform to customize the visualization, wherein the transforms modify information used by the data visualization platform to provide a customized visualization.
 10. The system of claim 9, wherein the transforms are data transforms, wherein the data transforms are operable to modify a format of the received data.
 11. The system of claim 9, wherein the transforms are geometry transforms, wherein the geometry transforms are operable to modify how the geometry are rendered.
 12. The system of claim 9, wherein the transforms are layout transforms, wherein the layout transforms are operable to modify how the geometry are defined to graphically represent the data series in the visualization.
 13. The system of claim 12, wherein the layout transforms are further operable to provide shared functionalities within the visualization.
 14. The system of claim 9, wherein the data visualization platform comprises a unidirectional pipeline in which the information flows, the unidirectional pipeline including: a data transform stage, corresponding to receiving the data and the surface description of the visualization; a layout transform stage, corresponding to creating the geometry; a geometry transform stage, corresponding to assembling the visualization; and wherein the extension module is further operable to insert the transforms at each of the stages.
 15. The system of claim 9, wherein the transforms include series layouts, wherein the series layouts include interfaces operable to isolate the series layouts from the system and provide the series layouts with only the data and a coordinate space from the surface description, wherein the series layout are operable to produce the geometry from the data and the coordinate space.
 16. A computing device operable for improving the functionality of a computer providing a data visualization according to an existing architecture, comprising: a processor; and a memory storage including instructions, which when executed by the processor cause the computing device to be operable to: manage a unidirectional pipelined flow of information, wherein the information is used to graphically representing data via a visualization, by inserting a transform into the pipelined flow to customize the visualization, wherein the unidirectional pipelined flow includes a data transform stage, a layout transform stage, and a geometry transform stage; receive the data and a surface description of the visualization, wherein the data includes data series, and wherein receiving the data and the surface description corresponds to the data transform stage; provide the data series of the data and the surface description to a series layout to create geometry to graphically represent each data series within the visualization, wherein creating geometry corresponds to the layout transform stage; transmit the geometry to a client operable to render the visualization, wherein transmitting corresponds to the geometry transform stage; and wherein the transform is inserted at one of the stages to customize one or more of the geometry.
 17. The computing device of claim 16, wherein the inserted transform is a data transform, wherein the data transform is inserted at the data transform stage and modifies a format of the received data, wherein the data according to the modified format is operable to produce the customized geometry.
 18. The computing device of claim 16, wherein the inserted transform is a layout transform, wherein the layout transform is determined to be appropriate for the data based on annotations included in the layout transform, wherein the layout transform is inserted at the layout transform stage and modifies a definition used to create the geometry to create the customized geometry.
 19. The computing device of claim 16, wherein the inserted transform is a geometry transform, wherein the geometry transform is inserted at the geometry transform stage and modifies how the customized geometry is rendered by the client.
 20. The computing device of claim 16, wherein each stage produces an output according to a normalized format, wherein the transform is operable to produce a transform output according to the same normalized format as the stage at which the transform is inserted. 